train_data

Dataset statistics

Number of variables	18
Number of observations	52516
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	6.9 MiB
Average record size in memory	137.0 B

Variable types

Text	7
Numeric	3
Categorical	4
DateTime	4

Alerts

`lifetime` is highly overall correlated with `lifetime_group`	High correlation
`lifetime_group` is highly overall correlated with `lifetime` and 1 other fields	High correlation
`status` is highly overall correlated with `lifetime_group`	High correlation
`status` is highly imbalanced (55.2%)	Imbalance
`countries_income_group` is highly imbalanced (59.3%)	Imbalance
`funding_total_usd` is highly skewed (γ1 = 120.7777503)	Skewed
`name` has unique values	Unique

Reproduction

Analysis started	2024-12-11 21:03:12.945936
Analysis finished	2024-12-11 21:03:18.093337
Duration	5.15 seconds
Software version	ydata-profiling vv4.12.1
Download configuration	config.json

name
Text

Unique

Distinct	52516
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	97
Median length	62
Mean length	12.101379
Min length	1

Characters and Unicode

Total characters	635516
Distinct characters	227
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	52516 ?
Unique (%)	100.0%

Sample

1st row	Lunchgate
2nd row	EarLens
3rd row	Reviva Pharmaceuticals
4th row	Sancilio and Company
5th row	WireTough Cylinders

Value	Count	Frequency (%)
technologies	1229	1.5%
inc	1127	1.3%
systems	724	0.9%
solutions	630	0.7%
group	559	0.7%
media	528	0.6%
technology	509	0.6%
medical	478	0.6%
the	463	0.5%
networks	418	0.5%
Other values (48375)	77834	92.1%

Most occurring characters

Value	Count	Frequency (%)
e	59710	9.4%
o	44019	6.9%
i	43013	6.8%
a	42156	6.6%
n	35157	5.5%
t	33927	5.3%
r	33837	5.3%
	31981	5.0%
s	26632	4.2%
l	25020	3.9%
Other values (217)	260064	40.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	635516	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	59710	9.4%
o	44019	6.9%
i	43013	6.8%
a	42156	6.6%
n	35157	5.5%
t	33927	5.3%
r	33837	5.3%
	31981	5.0%
s	26632	4.2%
l	25020	3.9%
Other values (217)	260064	40.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	635516	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	59710	9.4%
o	44019	6.9%
i	43013	6.8%
a	42156	6.6%
n	35157	5.5%
t	33927	5.3%
r	33837	5.3%
	31981	5.0%
s	26632	4.2%
l	25020	3.9%
Other values (217)	260064	40.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	635516	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	59710	9.4%
o	44019	6.9%
i	43013	6.8%
a	42156	6.6%
n	35157	5.5%
t	33927	5.3%
r	33837	5.3%
	31981	5.0%
s	26632	4.2%
l	25020	3.9%
Other values (217)	260064	40.9%

category_list
Text

Distinct	22106
Distinct (%)	42.1%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	639
Median length	248
Mean length	28.061219
Min length	2

Characters and Unicode

Total characters	1473663
Distinct characters	64
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	20140 ?
Unique (%)	38.4%

Sample

1st row	Online Reservations\|Restaurants
2nd row	Manufacturing\|Medical\|Medical Devices
3rd row	Biotechnology
4th row	Health Care
5th row	Manufacturing

Value	Count	Frequency (%)
software	5014	4.6%
and	3068	2.8%
biotechnology	2906	2.7%
no_category	2465	2.3%
health	2371	2.2%
media	2212	2.0%
curated	1747	1.6%
	1550	1.4%
technology	1504	1.4%
web	1244	1.1%
Other values (22412)	84503	77.8%

Most occurring characters

Value	Count	Frequency (%)
e	153667	10.4%
a	105223	7.1%
i	101104	6.9%
o	100039	6.8%
n	95579	6.5%
t	94208	6.4%
r	80897	5.5%
\|	70937	4.8%
s	62364	4.2%
l	58518	4.0%
Other values (54)	551127	37.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1473663	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	153667	10.4%
a	105223	7.1%
i	101104	6.9%
o	100039	6.8%
n	95579	6.5%
t	94208	6.4%
r	80897	5.5%
\|	70937	4.8%
s	62364	4.2%
l	58518	4.0%
Other values (54)	551127	37.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1473663	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	153667	10.4%
a	105223	7.1%
i	101104	6.9%
o	100039	6.8%
n	95579	6.5%
t	94208	6.4%
r	80897	5.5%
\|	70937	4.8%
s	62364	4.2%
l	58518	4.0%
Other values (54)	551127	37.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1473663	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	153667	10.4%
a	105223	7.1%
i	101104	6.9%
o	100039	6.8%
n	95579	6.5%
t	94208	6.4%
r	80897	5.5%
\|	70937	4.8%
s	62364	4.2%
l	58518	4.0%
Other values (54)	551127	37.4%

funding_total_usd
Real number (ℝ)

Skewed

Distinct	15555
Distinct (%)	29.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14978122

Minimum	1
Maximum	3.0079503 × 10¹⁰
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	410.4 KiB

Quantile statistics

Minimum	1
5-th percentile	37614
Q1	529721.25
median	1021239
Q3	7000000
95-th percentile	56052954
Maximum	3.0079503 × 10¹⁰
Range	3.0079503 × 10¹⁰
Interquartile range (IQR)	6470278.8

Descriptive statistics

Standard deviation	1.6836128 × 10⁸
Coefficient of variation (CV)	11.24048
Kurtosis	19920.68
Mean	14978122
Median Absolute Deviation (MAD)	971239
Skewness	120.77775
Sum	7.8659106 × 10¹¹
Variance	2.8345522 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
860000	9193	17.5%
1000000	899	1.7%
100000	786	1.5%
500000	772	1.5%
2927171	706	1.3%
2000000	651	1.2%
50000	628	1.2%
40000	545	1.0%
250000	500	1.0%
5000000	495	0.9%
Other values (15545)	37341	71.1%

Value	Count	Frequency (%)
1	1	< 0.1%
2	2	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
10	1	< 0.1%
12	1	< 0.1%
20	1	< 0.1%
29	1	< 0.1%
30	1	< 0.1%
50	1	< 0.1%

Value	Count	Frequency (%)
3.0079503 × 10¹⁰	1	< 0.1%
1.066494364 × 10¹⁰	1	< 0.1%
8207450000	1	< 0.1%
5820000000	1	< 0.1%
5800000000	1	< 0.1%
5162513431	1	< 0.1%
5150000000	1	< 0.1%
4812000000	1	< 0.1%
4745460219	1	< 0.1%
4630000000	1	< 0.1%

status
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

operating	47599
closed	4917

Length

Max length	9
Median length	9
Mean length	8.7191142
Min length	6

Characters and Unicode

Total characters	457893
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	operating
2nd row	operating
3rd row	operating
4th row	operating
5th row	operating

Common Values

Value	Count	Frequency (%)
operating	47599	90.6%
closed	4917	9.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
operating	47599	90.6%
closed	4917	9.4%

Most occurring characters

Value	Count	Frequency (%)
o	52516	11.5%
e	52516	11.5%
p	47599	10.4%
r	47599	10.4%
a	47599	10.4%
t	47599	10.4%
i	47599	10.4%
n	47599	10.4%
g	47599	10.4%
c	4917	1.1%
Other values (3)	14751	3.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	457893	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
o	52516	11.5%
e	52516	11.5%
p	47599	10.4%
r	47599	10.4%
a	47599	10.4%
t	47599	10.4%
i	47599	10.4%
n	47599	10.4%
g	47599	10.4%
c	4917	1.1%
Other values (3)	14751	3.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	457893	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
o	52516	11.5%
e	52516	11.5%
p	47599	10.4%
r	47599	10.4%
a	47599	10.4%
t	47599	10.4%
i	47599	10.4%
n	47599	10.4%
g	47599	10.4%
c	4917	1.1%
Other values (3)	14751	3.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	457893	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
o	52516	11.5%
e	52516	11.5%
p	47599	10.4%
r	47599	10.4%
a	47599	10.4%
t	47599	10.4%
i	47599	10.4%
n	47599	10.4%
g	47599	10.4%
c	4917	1.1%
Other values (3)	14751	3.2%

country_code
Text

Distinct	135
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	10
Median length	3
Mean length	3.7333765
Min length	3

Characters and Unicode

Total characters	196062
Distinct characters	34
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	22 ?
Unique (%)	< 0.1%

Sample

1st row	CHE
2nd row	USA
3rd row	USA
4th row	no_country
5th row	USA

Value	Count	Frequency (%)
usa	29702	56.6%
no_country	5502	10.5%
gbr	2925	5.6%
can	1540	2.9%
ind	1276	2.4%
chn	1240	2.4%
fra	916	1.7%
deu	834	1.6%
isr	767	1.5%
esp	607	1.2%
Other values (125)	7207	13.7%

Most occurring characters

Value	Count	Frequency (%)
A	33855	17.3%
S	32775	16.7%
U	31752	16.2%
n	11004	5.6%
o	11004	5.6%
R	6858	3.5%
N	5773	2.9%
r	5502	2.8%
y	5502	2.8%
t	5502	2.8%
Other values (24)	46535	23.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	196062	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	33855	17.3%
S	32775	16.7%
U	31752	16.2%
n	11004	5.6%
o	11004	5.6%
R	6858	3.5%
N	5773	2.9%
r	5502	2.8%
y	5502	2.8%
t	5502	2.8%
Other values (24)	46535	23.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	196062	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	33855	17.3%
S	32775	16.7%
U	31752	16.2%
n	11004	5.6%
o	11004	5.6%
R	6858	3.5%
N	5773	2.9%
r	5502	2.8%
y	5502	2.8%
t	5502	2.8%
Other values (24)	46535	23.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	196062	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	33855	17.3%
S	32775	16.7%
U	31752	16.2%
n	11004	5.6%
o	11004	5.6%
R	6858	3.5%
N	5773	2.9%
r	5502	2.8%
y	5502	2.8%
t	5502	2.8%
Other values (24)	46535	23.7%

state_code
Text

Distinct	301
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	8
Median length	2
Mean length	2.694893
Min length	1

Characters and Unicode

Total characters	141525
Distinct characters	43
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	44 ?
Unique (%)	0.1%

Sample

1st row	25
2nd row	CA
3rd row	CA
4th row	no_state
5th row	VA

Value	Count	Frequency (%)
ca	10219	19.5%
no_state	6763	12.9%
ny	3112	5.9%
ma	2020	3.8%
tx	1562	3.0%
h9	1510	2.9%
7	1095	2.1%
fl	1038	2.0%
wa	997	1.9%
2	913	1.7%
Other values (291)	23287	44.3%

Most occurring characters

Value	Count	Frequency (%)
A	16811	11.9%
t	13526	9.6%
C	12894	9.1%
n	6763	4.8%
o	6763	4.8%
_	6763	4.8%
s	6763	4.8%
a	6763	4.8%
e	6763	4.8%
N	6498	4.6%
Other values (33)	51218	36.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	141525	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
A	16811	11.9%
t	13526	9.6%
C	12894	9.1%
n	6763	4.8%
o	6763	4.8%
_	6763	4.8%
s	6763	4.8%
a	6763	4.8%
e	6763	4.8%
N	6498	4.6%
Other values (33)	51218	36.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	141525	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
A	16811	11.9%
t	13526	9.6%
C	12894	9.1%
n	6763	4.8%
o	6763	4.8%
_	6763	4.8%
s	6763	4.8%
a	6763	4.8%
e	6763	4.8%
N	6498	4.6%
Other values (33)	51218	36.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	141525	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
A	16811	11.9%
t	13526	9.6%
C	12894	9.1%
n	6763	4.8%
o	6763	4.8%
_	6763	4.8%
s	6763	4.8%
a	6763	4.8%
e	6763	4.8%
N	6498	4.6%
Other values (33)	51218	36.2%

region
Text

Distinct	1037
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	38
Median length	26
Mean length	9.2023955
Min length	3

Characters and Unicode

Total characters	483273
Distinct characters	67
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	220 ?
Unique (%)	0.4%

Sample

1st row	Zurich
2nd row	SF Bay Area
3rd row	SF Bay Area
4th row	no_region
5th row	VA - Other

Value	Count	Frequency (%)
bay	6992	8.1%
sf	6970	8.1%
area	6970	8.1%
no_region	6359	7.4%
city	3404	3.9%
new	3285	3.8%
york	2859	3.3%
	2825	3.3%
other	2556	3.0%
boston	1891	2.2%
Other values (1135)	42302	49.0%

Most occurring characters

Value	Count	Frequency (%)
e	42283	8.7%
o	41619	8.6%
a	39740	8.2%
n	38761	8.0%
	33897	7.0%
r	30705	6.4%
i	27327	5.7%
t	20348	4.2%
l	15248	3.2%
g	15119	3.1%
Other values (57)	178226	36.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	483273	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	42283	8.7%
o	41619	8.6%
a	39740	8.2%
n	38761	8.0%
	33897	7.0%
r	30705	6.4%
i	27327	5.7%
t	20348	4.2%
l	15248	3.2%
g	15119	3.1%
Other values (57)	178226	36.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	483273	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	42283	8.7%
o	41619	8.6%
a	39740	8.2%
n	38761	8.0%
	33897	7.0%
r	30705	6.4%
i	27327	5.7%
t	20348	4.2%
l	15248	3.2%
g	15119	3.1%
Other values (57)	178226	36.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	483273	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	42283	8.7%
o	41619	8.6%
a	39740	8.2%
n	38761	8.0%
	33897	7.0%
r	30705	6.4%
i	27327	5.7%
t	20348	4.2%
l	15248	3.2%
g	15119	3.1%
Other values (57)	178226	36.9%

city
Text

Distinct	4478
Distinct (%)	8.5%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	32
Median length	27
Mean length	8.4619545
Min length	2

Characters and Unicode

Total characters	444388
Distinct characters	88
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2304 ?
Unique (%)	4.4%

Sample

1st row	Zürich
2nd row	Redwood City
3rd row	San Jose
4th row	no_city
5th row	Bristol

Value	Count	Frequency (%)
no_city	6359	9.3%
san	4282	6.3%
francisco	2884	4.2%
new	2756	4.0%
york	2493	3.6%
london	1521	2.2%
city	845	1.2%
los	727	1.1%
santa	710	1.0%
palo	612	0.9%
Other values (4361)	45191	66.1%

Most occurring characters

Value	Count	Frequency (%)
n	41983	9.4%
o	41535	9.3%
a	39037	8.8%
e	30594	6.9%
i	30444	6.9%
t	23970	5.4%
r	22491	5.1%
l	20382	4.6%
c	17296	3.9%
s	15911	3.6%
Other values (78)	160745	36.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	444388	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	41983	9.4%
o	41535	9.3%
a	39037	8.8%
e	30594	6.9%
i	30444	6.9%
t	23970	5.4%
r	22491	5.1%
l	20382	4.6%
c	17296	3.9%
s	15911	3.6%
Other values (78)	160745	36.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	444388	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	41983	9.4%
o	41535	9.3%
a	39037	8.8%
e	30594	6.9%
i	30444	6.9%
t	23970	5.4%
r	22491	5.1%
l	20382	4.6%
c	17296	3.9%
s	15911	3.6%
Other values (78)	160745	36.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	444388	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	41983	9.4%
o	41535	9.3%
a	39037	8.8%
e	30594	6.9%
i	30444	6.9%
t	23970	5.4%
r	22491	5.1%
l	20382	4.6%
c	17296	3.9%
s	15911	3.6%
Other values (78)	160745	36.2%

funding_rounds
Real number (ℝ)

Distinct	19
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.7406695

Minimum	1
Maximum	19
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	410.4 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	2
95-th percentile	4
Maximum	19
Range	18
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.3745222
Coefficient of variation (CV)	0.78965143
Kurtosis	14.293641
Mean	1.7406695
Median Absolute Deviation (MAD)	0
Skewness	3.0690907
Sum	91413
Variance	1.8893112
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=19)

Value	Count	Frequency (%)
1	33489	63.8%
2	9816	18.7%
3	4450	8.5%
4	2189	4.2%
5	1168	2.2%
6	616	1.2%
7	341	0.6%
8	175	0.3%
9	109	0.2%
10	63	0.1%
Other values (9)	100	0.2%

Value	Count	Frequency (%)
1	33489	63.8%
2	9816	18.7%
3	4450	8.5%
4	2189	4.2%
5	1168	2.2%
6	616	1.2%
7	341	0.6%
8	175	0.3%
9	109	0.2%
10	63	0.1%

Value	Count	Frequency (%)
19	1	< 0.1%
18	3	< 0.1%
17	3	< 0.1%
16	6	< 0.1%
15	5	< 0.1%
14	5	< 0.1%
13	9	< 0.1%
12	22	< 0.1%
11	46	0.1%
10	63	0.1%

founded_at
Date

Distinct	5402
Distinct (%)	10.3%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Minimum	1970-02-05 00:00:00
Maximum	2016-04-02 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

first_funding_at
Date

Distinct	4603
Distinct (%)	8.8%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Minimum	1977-05-15 00:00:00
Maximum	2015-12-05 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

last_funding_at
Date

Distinct	4305
Distinct (%)	8.2%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Minimum	1977-05-15 00:00:00
Maximum	2015-12-07 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

closed_at
Date

Distinct	3009
Distinct (%)	5.7%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Minimum	1983-10-06 00:00:00
Maximum	2018-01-01 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

lifetime
Real number (ℝ)

High correlation

Distinct	5738
Distinct (%)	10.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3140.8281

Minimum	19
Maximum	17378
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	410.4 KiB

Quantile statistics

Minimum	19
5-th percentile	991
Q1	1739
median	2557
Q3	4018
95-th percentile	7277.5
Maximum	17378
Range	17359
Interquartile range (IQR)	2279

Descriptive statistics

Standard deviation	2147.8211
Coefficient of variation (CV)	0.6838391
Kurtosis	5.840143
Mean	3140.8281
Median Absolute Deviation (MAD)	1004
Skewness	2.0047053
Sum	1.6494373 × 10⁸
Variance	4613135.3
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2192	2069	3.9%
1826	1896	3.6%
2557	1882	3.6%
2922	1556	3.0%
3287	1370	2.6%
1461	1225	2.3%
4018	1096	2.1%
3653	1030	2.0%
4383	894	1.7%
4748	801	1.5%
Other values (5728)	38697	73.7%

Value	Count	Frequency (%)
19	1	< 0.1%
57	1	< 0.1%
58	1	< 0.1%
70	1	< 0.1%
71	1	< 0.1%
90	1	< 0.1%
112	1	< 0.1%
119	1	< 0.1%
122	1	< 0.1%
126	1	< 0.1%

Value	Count	Frequency (%)
17378	1	< 0.1%
17167	12	< 0.1%
17079	1	< 0.1%
17004	1	< 0.1%
16802	13	< 0.1%
16711	1	< 0.1%
16609	1	< 0.1%
16436	9	< 0.1%
16346	1	< 0.1%
16316	1	< 0.1%

lifetime_group
Categorical

High correlation

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	51.6 KiB

>5 лет	38183
3-5 лет	10854
1-3 лет	3395
<1 года	84

Length

Max length	7
Median length	6
Mean length	6.2729263
Min length	6

Characters and Unicode

Total characters	329429
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	>5 лет
2nd row	>5 лет
3rd row	>5 лет
4th row	>5 лет
5th row	>5 лет

Common Values

Value	Count	Frequency (%)
>5 лет	38183	72.7%
3-5 лет	10854	20.7%
1-3 лет	3395	6.5%
<1 года	84	0.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
лет	52432	49.9%
5	38183	36.4%
3-5	10854	10.3%
1-3	3395	3.2%
1	84	0.1%
года	84	0.1%

Most occurring characters

Value	Count	Frequency (%)
	52516	15.9%
л	52432	15.9%
е	52432	15.9%
т	52432	15.9%
5	49037	14.9%
>	38183	11.6%
3	14249	4.3%
-	14249	4.3%
1	3479	1.1%
<	84	< 0.1%
Other values (4)	336	0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	329429	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	52516	15.9%
л	52432	15.9%
е	52432	15.9%
т	52432	15.9%
5	49037	14.9%
>	38183	11.6%
3	14249	4.3%
-	14249	4.3%
1	3479	1.1%
<	84	< 0.1%
Other values (4)	336	0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	329429	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	52516	15.9%
л	52432	15.9%
е	52432	15.9%
т	52432	15.9%
5	49037	14.9%
>	38183	11.6%
3	14249	4.3%
-	14249	4.3%
1	3479	1.1%
<	84	< 0.1%
Other values (4)	336	0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	329429	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	52516	15.9%
л	52432	15.9%
е	52432	15.9%
т	52432	15.9%
5	49037	14.9%
>	38183	11.6%
3	14249	4.3%
-	14249	4.3%
1	3479	1.1%
<	84	< 0.1%
Other values (4)	336	0.1%

category_first_word
Text

Distinct	708
Distinct (%)	1.3%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

Length

Max length	37
Median length	29
Mean length	11.315313
Min length	2

Characters and Unicode

Total characters	594235
Distinct characters	37
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	73 ?
Unique (%)	0.1%

Sample

1st row	online reservations
2nd row	manufacturing
3rd row	biotechnology
4th row	health care
5th row	manufacturing

Value	Count	Frequency (%)
software	5342	7.3%
biotechnology	3593	4.9%
no_category	2465	3.4%
health	2257	3.1%
e-commerce	2203	3.0%
web	2054	2.8%
advertising	2050	2.8%
technology	1834	2.5%
curated	1747	2.4%
analytics	1542	2.1%
Other values (674)	47791	65.6%

Most occurring characters

Value	Count	Frequency (%)
e	68873	11.6%
o	48621	8.2%
a	48045	8.1%
t	45957	7.7%
n	42875	7.2%
i	39652	6.7%
r	36967	6.2%
c	36608	6.2%
s	34490	5.8%
l	25002	4.2%
Other values (27)	167145	28.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	594235	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	68873	11.6%
o	48621	8.2%
a	48045	8.1%
t	45957	7.7%
n	42875	7.2%
i	39652	6.7%
r	36967	6.2%
c	36608	6.2%
s	34490	5.8%
l	25002	4.2%
Other values (27)	167145	28.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	594235	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	68873	11.6%
o	48621	8.2%
a	48045	8.1%
t	45957	7.7%
n	42875	7.2%
i	39652	6.7%
r	36967	6.2%
c	36608	6.2%
s	34490	5.8%
l	25002	4.2%
Other values (27)	167145	28.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	594235	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	68873	11.6%
o	48621	8.2%
a	48045	8.1%
t	45957	7.7%
n	42875	7.2%
i	39652	6.7%
r	36967	6.2%
c	36608	6.2%
s	34490	5.8%
l	25002	4.2%
Other values (27)	167145	28.1%

activity_group
Categorical

Distinct	20
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

J	19831
C	8187
M	4694
R	2950
Q	2908
Other values (15)	13946

Length

Max length	11
Median length	1
Mean length	1.4693808
Min length	1

Characters and Unicode

Total characters	77166
Distinct characters	22
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	J
2nd row	C
3rd row	C
4th row	Q
5th row	C

Common Values

Value	Count	Frequency (%)
J	19831	37.8%
C	8187	15.6%
M	4694	8.9%
R	2950	5.6%
Q	2908	5.5%
S	2755	5.2%
G	2727	5.2%
NO_CATEGORY	2465	4.7%
K	2015	3.8%
P	1238	2.4%
Other values (10)	2746	5.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
j	19831	37.8%
c	8187	15.6%
m	4694	8.9%
r	2950	5.6%
q	2908	5.5%
s	2755	5.2%
g	2727	5.2%
no_category	2465	4.7%
k	2015	3.8%
p	1238	2.4%
Other values (10)	2746	5.2%

Most occurring characters

Value	Count	Frequency (%)
J	19831	25.7%
C	10652	13.8%
R	5415	7.0%
G	5192	6.7%
O	5000	6.5%
M	4694	6.1%
N	3057	4.0%
Q	2908	3.8%
S	2755	3.6%
A	2613	3.4%
Other values (12)	15049	19.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	77166	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
J	19831	25.7%
C	10652	13.8%
R	5415	7.0%
G	5192	6.7%
O	5000	6.5%
M	4694	6.1%
N	3057	4.0%
Q	2908	3.8%
S	2755	3.6%
A	2613	3.4%
Other values (12)	15049	19.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	77166	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
J	19831	25.7%
C	10652	13.8%
R	5415	7.0%
G	5192	6.7%
O	5000	6.5%
M	4694	6.1%
N	3057	4.0%
Q	2908	3.8%
S	2755	3.6%
A	2613	3.4%
Other values (12)	15049	19.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	77166	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
J	19831	25.7%
C	10652	13.8%
R	5415	7.0%
G	5192	6.7%
O	5000	6.5%
M	4694	6.1%
N	3057	4.0%
Q	2908	3.8%
S	2755	3.6%
A	2613	3.4%
Other values (12)	15049	19.5%

countries_income_group
Categorical

Imbalance

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	410.4 KiB

High income	42920
NO_COUNTRY	5502
Upper middle income	2463
Lower middle income	1611
Low income	20

Length

Max length	19
Median length	11
Mean length	11.515462
Min length	10

Characters and Unicode

Total characters	604746
Distinct characters	24
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High income
2nd row	High income
3rd row	High income
4th row	NO_COUNTRY
5th row	High income

Common Values

Value	Count	Frequency (%)
High income	42920	81.7%
NO_COUNTRY	5502	10.5%
Upper middle income	2463	4.7%
Lower middle income	1611	3.1%
Low income	20	< 0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
income	47014	45.4%
high	42920	41.4%
no_country	5502	5.3%
middle	4074	3.9%
upper	2463	2.4%
lower	1611	1.6%
low	20	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
i	94008	15.5%
e	55162	9.1%
	51088	8.4%
m	51088	8.4%
o	48645	8.0%
n	47014	7.8%
c	47014	7.8%
H	42920	7.1%
g	42920	7.1%
h	42920	7.1%
Other values (14)	81967	13.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	604746	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
i	94008	15.5%
e	55162	9.1%
	51088	8.4%
m	51088	8.4%
o	48645	8.0%
n	47014	7.8%
c	47014	7.8%
H	42920	7.1%
g	42920	7.1%
h	42920	7.1%
Other values (14)	81967	13.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	604746	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
i	94008	15.5%
e	55162	9.1%
	51088	8.4%
m	51088	8.4%
o	48645	8.0%
n	47014	7.8%
c	47014	7.8%
H	42920	7.1%
g	42920	7.1%
h	42920	7.1%
Other values (14)	81967	13.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	604746	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
i	94008	15.5%
e	55162	9.1%
	51088	8.4%
m	51088	8.4%
o	48645	8.0%
n	47014	7.8%
c	47014	7.8%
H	42920	7.1%
g	42920	7.1%
h	42920	7.1%
Other values (14)	81967	13.6%

	activity_group	countries_income_group	funding_rounds	funding_total_usd	lifetime	lifetime_group	status
activity_group	1.000	0.158	0.046	0.015	0.076	0.119	0.162
countries_income_group	0.158	1.000	0.062	0.014	0.087	0.113	0.166
funding_rounds	0.046	0.062	1.000	0.467	0.215	0.113	0.076
funding_total_usd	0.015	0.014	0.467	1.000	0.407	0.000	0.000
lifetime	0.076	0.087	0.215	0.407	1.000	0.550	0.413
lifetime_group	0.119	0.113	0.113	0.000	0.550	1.000	0.666
status	0.162	0.166	0.076	0.000	0.413	0.666	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

	name	category_list	funding_total_usd	status	country_code	state_code	region	city	funding_rounds	founded_at	first_funding_at	last_funding_at	closed_at	lifetime	lifetime_group	category_first_word	activity_group	countries_income_group
0	Lunchgate	Online Reservations\|Restaurants	828626.0	operating	CHE	25	Zurich	Zürich	2	2009-10-17	2011-05-01	2014-12-01	2018-01-01	2998	>5 лет	online reservations	J	High income
1	EarLens	Manufacturing\|Medical\|Medical Devices	42935019.0	operating	USA	CA	SF Bay Area	Redwood City	4	2005-01-01	2010-05-04	2014-02-25	2018-01-01	4748	>5 лет	manufacturing	C	High income
2	Reviva Pharmaceuticals	Biotechnology	35456381.0	operating	USA	CA	SF Bay Area	San Jose	3	2006-01-01	2012-08-20	2014-07-02	2018-01-01	4383	>5 лет	biotechnology	C	High income
3	Sancilio and Company	Health Care	22250000.0	operating	no_country	no_state	no_region	no_city	3	2004-01-01	2011-09-01	2014-07-18	2018-01-01	5114	>5 лет	health care	Q	NO_COUNTRY
4	WireTough Cylinders	Manufacturing	860000.0	operating	USA	VA	VA - Other	Bristol	1	2010-05-12	2012-02-01	2012-02-01	2018-01-01	2791	>5 лет	manufacturing	C	High income
5	Connected Sports Ventures	Mobile	4300000.0	operating	USA	NJ	Newark	Princeton	1	2011-04-16	2012-11-12	2012-11-12	2018-01-01	2452	>5 лет	mobile	J	High income
6	Attensity	Analytics\|Business Analytics\|Social CRM\|Social Media Monitoring\|Software	90000000.0	operating	USA	CA	SF Bay Area	Redwood City	1	2000-01-01	2014-05-14	2014-05-14	2018-01-01	6575	>5 лет	analytics	J	High income
7	Mesh Networks	Software	4300000.0	operating	USA	TX	Houston	Houston	1	2005-01-01	2014-11-09	2014-11-09	2018-01-01	4748	>5 лет	software	J	High income
8	AngioScore	Biotechnology	42000000.0	operating	USA	CA	SF Bay Area	Fremont	2	2003-01-01	2007-10-09	2011-04-20	2018-01-01	5479	>5 лет	biotechnology	C	High income
9	Vidatronic	Semiconductors	1250500.0	operating	USA	TX	Austin	College Station	2	2010-01-01	2011-08-23	2013-03-21	2018-01-01	2922	>5 лет	semiconductors	C	High income

	name	category_list	funding_total_usd	status	country_code	state_code	region	city	funding_rounds	founded_at	first_funding_at	last_funding_at	closed_at	lifetime	lifetime_group	category_first_word	activity_group	countries_income_group
52506	Dignify Therapeutics	Biotechnology	3209000.0	operating	USA	NC	Raleigh	Raleigh	3	2013-01-01	2014-02-05	2015-02-04	2018-01-01	1826	>5 лет	biotechnology	C	High income
52507	Proactive Comfort	Medical	860000.0	operating	USA	MD	Baltimore	Centreville	1	2009-10-16	2011-01-20	2011-01-20	2018-01-01	2999	>5 лет	medical	Q	High income
52508	ScramCard	no_category	860000.0	operating	HKG	no_state	Hong Kong	Hong Kong	1	2013-01-01	2015-11-20	2015-11-20	2018-01-01	1826	>5 лет	no_category	NO_CATEGORY	High income
52509	Visionary Mobile	Biotechnology	1570000.0	operating	USA	OR	Salem, Oregon	Corvallis	3	2010-01-01	2011-09-20	2012-04-11	2018-01-01	2922	>5 лет	biotechnology	C	High income
52510	Shanghai Media Group	News	205600000.0	operating	CHN	23	Shanghai	Shanghai	2	2001-01-01	2008-04-15	2015-06-04	2018-01-01	6209	>5 лет	news	J	Upper middle income
52511	Videostream	Entertainment	860000.0	operating	CAN	ON	Toronto	Kitchener	1	2012-01-01	2014-03-01	2014-03-01	2018-01-01	2192	>5 лет	entertainment	R	High income
52512	Hello Curry	Hospitality	500000.0	operating	IND	2	Hyderabad	Hyderabad	1	2013-08-25	2014-03-07	2014-03-07	2018-01-01	1590	3-5 лет	hospitality	I	Lower middle income
52513	Taskforce	Email\|Messaging\|Productivity Software	50000.0	operating	USA	CA	SF Bay Area	San Francisco	3	2010-07-01	2009-06-14	2011-01-01	2018-01-01	2741	>5 лет	email	J	High income
52514	NetScaler	Security	13000000.0	operating	USA	CA	SF Bay Area	San Jose	6	1997-12-01	1998-11-30	2004-03-01	2018-01-01	7336	>5 лет	security	J	High income
52515	Apparcando	Online Rental\|Parking\|Price Comparison	270820.0	operating	ESP	60	Valencia	Valencia	1	2012-08-11	2014-06-13	2014-06-13	2018-01-01	1969	>5 лет	online rental	G	High income

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories